Abstract
Grid computing the job scheduling is the major issue that needs to be addressed prior to the development of a grid system or architecture. Scheduling is the user’s job to apropos resources in the grid environment. Grid computing has got a very wide domain in its application and thus induces various research opportunities that are generally spread over many areas of distributed computing and computer science. The cardinal point of scheduling is being attaining apex attainable performance and to satisfy the application requirements with computing resources at exposure. This paper posits techniques of using different scheduling techniques for increasing the efficacy of the grid system. This hybrid scheduler could enable the grid system to reduce the execution time. This paper also proposes an architecture which could be implemented ensuring the optimal results in the grid environment. This adaptive scheduler would possibly combine the pros of two scheduling strategies to produce a hybrid scheduling strategy which could cater the ever changing workload encountered by the gird system. The main objective of the proposed system is to reduce to overall job execution time and processor utilization time.
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Sinha, P., Aeishel, G., Jayapandian, N. (2020). Computational Model for Hybrid Job Scheduling in Grid Computing. In: Balaji, S., Rocha, Á., Chung, YN. (eds) Intelligent Communication Technologies and Virtual Mobile Networks. ICICV 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 33. Springer, Cham. https://doi.org/10.1007/978-3-030-28364-3_38
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DOI: https://doi.org/10.1007/978-3-030-28364-3_38
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